Communication device and a method for hybrid beamforming

ABSTRACT

A method and a communication device adapted for designing a hybrid beamforming (HB) precoding used in a mobile communication system with an antenna array, the method including aggregating spatial channel vectors received by the antenna array; performing a linear factorization of the aggregation; truncating the linear factorization to generate truncated channels; and designing the HB precoding based on the truncated channels, wherein the HB precoding includes a linearly generated analog beamforming component and a linearly generated digital beamforming component.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a national stage entry according to 35 U.S.C. § 371of PCT Application No. PCT/CN2016/100222 filed on Sep. 27, 2016, whichis incorporated herein by reference in its entirety.

TECHNICAL FIELD

Various aspects of this disclosure relate generally to a method and adevice for wireless communications.

BACKGROUND

Hybrid beamforming systems include elements of in both the analog anddigital domains. Antenna ports with radio frequency (RF) chains providethe full capability of digital beamforming while arrays of antennaelements with phase shifters provide the capability of analogbeamforming. Hybrid beamforming is expected to achieve the highperformance of full digital massive multiple input multiple output(MIMO) while minimizing the high costs associated with the RF chains indigital beamforming.

Current solutions to hybrid precoding design for a hybrid beamformingsystem include a fixed analog beamforming that is set according to thedown tilt of the antenna array or generating analog and digitalbeamforming by nonlinear iteration optimizations/exhaustive search. Theformer has the benefit of a low precoding complexity, but it cannotachieve high system performance. The latter can achieve high systemperformance, but it has an extremely high precoding complexity,especially for an orthogonal frequency-division multiple access (OFDMA)multi-user MIMO system. Due to multiple users and multiple subcarrierswhich need to be considered, these iteration optimization-based hybridprecoding techniques experience unacceptably high computationalcomplexity. Moreover, convergence of the iterations cannot beguaranteed.

The subject matter disclosed herein provides a device and a method forhybrid beamforming precoding with high system performance whileminimizing precoding complexity.

BRIEF DESCRIPTION OF THE DRAWINGS

In the drawings, like reference characters generally refer to the sameparts throughout the different views. The drawings are not necessarilyto scale, emphasis instead generally being placed upon illustrating theprinciples of the invention. In the following description, variousembodiments of the invention are described with reference to thefollowing drawings, in which:

FIG. 1 shows a communication network in an aspect of this disclosure.

FIG. 2 shows a communication network in an aspect of this disclosure.

FIG. 3 shows an internal arrangement for a device in an aspect of thisdisclosure.

FIG. 4 shows a block diagram showing a hybrid precoding in an aspect ofthis disclosure.

FIG. 5 shows a block diagram for a channel truncation in an aspect ofthis disclosure.

FIG. 6 shows a block diagram for analog beamforming generation in anaspect of this disclosure.

FIG. 7 shows a block diagram for digital beamforming generation in anaspect of this disclosure.

FIG. 8 shows a graph with simulation results for a designed hybridprecoding in an aspect this disclosure.

FIG. 9 shows a circuit diagram for a communication device in an aspectof this disclosure.

FIG. 10 shows a flowchart for a method to design a hybrid beamformingprecoding in an aspect of this disclosure.

DESCRIPTION

The following details description refers to the accompanying drawingsthat show, by way of illustration, specific details and embodiments inwhich the invention may be practiced.

The word “exemplary” is used herein to mean “serving as an example,instance, or illustration”. Any embodiment or design described herein as“exemplary” is not necessarily to be construed as preferred oradvantageous over other embodiments or designs.

The words “plural” and “multiple” in the description and the claims, ifany, are used to expressly refer to a quantity greater than one.Accordingly, any phrases explicitly invoking the aforementioned words(e.g. “a plurality of [objects]”, “multiple [objects]”) referring to aquantity of objects is intended to expressly refer more than one of thesaid objects. The terms “group”, “set”, “collection”, “series”,“sequence”, “grouping”, “selection”, etc., and the like in thedescription and in the claims, if any, are used to refer to a quantityequal to or greater than one, i.e. one or more. Accordingly, the phrases“a group of [objects]”, “a set of [objects]”, “a collection of[objects]”, “a series of [objects]”, “a sequence of [objects]”, “agrouping of [objects]”, “a selection of [objects]”, “[object] group”,“[object] set”, “[object] collection”, “[object] series”, “[object]sequence”, “[object] grouping”, “[object] selection”, etc., used hereinin relation to a quantity of objects is intended to refer to a quantityof one or more of said objects. It is appreciated that unless directlyreferred to with an explicitly stated plural quantity (e.g. “two[objects]” “three of the [objects]”, “ten or more [objects]”, “at leastfour [objects]”, etc.) or express use of the words “plural”, “multiple”,or similar phrases, references to quantities of objects are intended torefer to one or more of said objects.

A “circuit” as used herein is understood as any kind oflogic-implementing entity, which may include special-purpose hardware ora processor executing software. A circuit may thus be an analog circuit,digital circuit, mixed-signal circuit, logic circuit, processor,microprocessor, Central Processing Unit (CPU), Graphics Processing Unit(GPU), Digital Signal Processor (DSP), Field Programmable Gate Array(FPGA), integrated circuit, Application Specific Integrated Circuit(ASIC), etc., or any combination thereof. Any other kind ofimplementation of the respective functions which will be described belowin further detail may also be understood as a “circuit”. It isunderstood that any two (or more) of the circuits detailed herein may berealized as a single circuit with substantially equivalentfunctionality, and conversely that any single circuit detailed hereinmay be realized as two (or more) separate circuits with substantiallyequivalent functionality. Additionally, references to a “circuit” mayrefer to two or more circuits that collectively form a single circuit.The term “circuit arrangement” may refer to a single circuit, acollection of circuits, and/or an electronic device composed of one ormore circuits.

A “processing circuit” (or equivalently “processing circuitry” or“processer”) as used herein is understood as referring to any circuitthat performs an operation(s) on signal(s), such as e.g. any circuitthat performs processing on an electrical signal or an optical signal. Aprocessing circuit may thus refer to any analog or digital circuitrythat alters a characteristic or property of an electrical or opticalsignal, which may include analog and/or digital data. A processingcircuit may thus refer to an analog circuit (explicitly referred to as“analog processing circuit(ry)”), digital circuit (explicitly referredto as “digital processing circuit(ry)”), logic circuit, processor,microprocessor, Central Processing Unit (CPU), Graphics Processing Unit(GPU), Digital Signal Processor (DSP), Field Programmable Gate Array(FPGA), integrated circuit, Application Specific Integrated Circuit(ASIC), etc., or any combination thereof. Accordingly, a processingcircuit may refer to a circuit that performs processing on an electricalor optical signal as hardware or as software, such as software executedon hardware (e.g. a processor or microprocessor). As utilized herein,“digital processing circuit(ry)” may refer to a circuit implementedusing digital logic that performs processing on a signal, e.g. anelectrical or optical signal, which may include logic circuit(s),processor(s), scalar processor(s), vector processor(s),microprocessor(s), controller(s), microcontroller(s), Central ProcessingUnit(s) (CPU), Graphics Processing Unit(s) (GPU), Digital SignalProcessor(s) (DSP), Field Programmable Gate Array(s) (FPGA), integratedcircuit(s), Application Specific Integrated Circuit(s) (ASIC), or anycombination thereof. Furthermore, it is understood that a single aprocessing circuit may be equivalently split into two separateprocessing circuits, and conversely that two separate processingcircuits may be combined into a single equivalent processing circuit.

As used herein, “memory” may be understood as an electrical component inwhich data or information can be stored for retrieval. References to“memory” included herein may thus be understood as referring to volatileor non-volatile memory, including random access memory (RAM), read-onlymemory (ROM), flash memory, solid-state storage, magnetic tape, harddisk drive, optical drive, etc., or any combination thereof.Furthermore, it is appreciated that registers, shift registers,processor registers, data buffers, etc., are also embraced herein by the“term” memory. It is appreciated that a single component referred to as“memory” or “a memory” may be composed of more than one different typeof memory, and thus may refer to a collective component comprising oneor more types of memory. It is readily understood that any single memory“component” may be distributed or/separated multiple substantiallyequivalent memory components, and vice versa. Furthermore, it isappreciated that while “memory” may be depicted, such as in thedrawings, as separate from one or more other components, it isunderstood that memory may be integrated within another component, suchas on a common integrated chip.

As used herein, a “cell”, in the context of telecommunications, may beunderstood as a sector served by a base station. Accordingly, a cell maybe a set of geographically co-located antennas that correspond to aparticular sector of a base station. A base station may thus serve oneor more “cells” (or “sectors”), where each cell is characterized by adistinct communication channel. An “inter-cell handover” may beunderstood as a handover from a first “cell” to a second “cell”, wherethe first “cell” is different from the second “cell”. “Inter-cellhandovers” may be characterized as either “inter-base station handovers”or “intra-base station handovers”. “Inter-base station handovers” may beunderstood as a handover from a first “cell” to a second “cell”, wherethe first “cell” is provided at a first base station and the second“cell” is provided at a second, different, base station. “Intra-basestation handovers” may be understood as a handover from a first “cell”to a second “cell”, where the first “cell” is provided at the same basestation as the second “cell”. A “serving cell” may be understood as a“cell” that a mobile terminal is currently connected to according to themobile communications protocols of the associated mobile communicationsnetwork standard. Furthermore, the term “cell” may be utilized to referto any of a macrocell, microcell, picocell, or femtocell, etc.

The term “base station”, used in reference to an access point of amobile communications network, may be understood as a macro-basestation, micro-base station, Node B, evolved Node B (eNodeB, eNB), HomeeNodeB, Remote Radio Head (RRH), or relay point, etc.

For purposes of this disclosure, radio communication technologies may beclassified as one of a Short Range radio communication technology,Metropolitan Area System radio communication technology, or CellularWide Area radio communication technology. Short Range radiocommunication technologies include Bluetooth, WLAN (e.g. according toany IEEE 802.11 standard), and other similar radio communicationtechnologies. Metropolitan Area System radio communication technologiesinclude Worldwide Interoperability for Microwave Access (WiMax) (e.g.according to an IEEE 802.16 radio communication standard, e.g. WiMaxfixed or WiMax mobile) and other similar radio communicationtechnologies. Cellular Wide Area radio communication technologiesinclude Global System for Mobile Communications (GSM), Code DivisionMultiple Access 2000 (CDMA2000), Universal Mobile TelecommunicationsSystem (UMTS), Long Term Evolution (LTE), General Packet Radio Service(GPRS), Evolution-Data Optimized (EV-DO), Enhanced Data Rates for GSMEvolution (EDGE), High Speed Packet Access (HSPA), etc., and othersimilar radio communication technologies. Cellular Wide Area radiocommunication technologies also include “small cells” of suchtechnologies, such as microcells, femtocells, and picocells. CellularWide Area radio communication technologies may be generally referred toherein as “cellular” communication technologies. It is understood thatexemplary scenarios detailed herein are demonstrative in nature, andaccordingly may be similarly applied to various other mobilecommunication technologies, both existing and not yet formulated,particularly in cases where such mobile communication technologies sharesimilar features as disclosed regarding the following examples.

The term “network” as utilized herein, e.g. in reference to acommunication network such as a mobile communication network, isintended to encompass both an access component of a network (e.g. aradio access network (RAN) component) and a core component of a network(e.g. a core network component).

Unless explicitly specified, the term “transmit” encompasses both direct(point-to-point) and indirect transmission (via one or more intermediarypoints). Similarly, the term “receive” encompasses both direct andindirect reception. The term “communicate” encompasses one or both oftransmitting and receiving, i.e. unidirectional or bidirectionalcommunication in one or both of the incoming and outgoing directions.The term “calculate” encompass both ‘direct’ calculations via amathematical expression/formula/relationship and ‘indirect’ calculationsvia lookup tables and other array indexing or searching operations.

It is appreciated that any vector and/or matrix notation utilized hereinis exemplary in nature and is employed solely for purposes ofexplanation. Accordingly, it is understood that the approaches detailedin this disclosure are not limited to being implemented solely usingvectors and/or matrices, and that the associated processes andcomputations may be equivalently performed with respect to sets,sequences, groups, etc., of data, observations, information, signals,samples, symbols, elements, etc. Furthermore, it is appreciated thatreferences to a “vector” may refer to a vector of any size ororientation, e.g. including a 1×1 vector (e.g. a scalar), a 1×M vector(e.g. a row vector), and an M×1 vector (e.g. a column vector).Similarly, it is appreciated that references to a “matrix” may refer tomatrix of any size or orientation, e.g. including a 1×1 matrix (e.g. ascalar), a 1×M matrix (e.g. a row vector), and an M×1 matrix (e.g. acolumn vector).

The subject matter disclosed herein provides a device and method todesign hybrid precoding with a linear algorithm, and in doing so,provide high system performance with a linear precoding complexity.

In a hybrid beamforming system, the number of antenna ports (i.e. the RFchains) is less than the number of antenna elements. This factor posesan additional constraint on hybrid precoding. Moreover, the hybridprecoding has to consider must consider multi-user OFDMA transmission,whereas analog beamforming is wideband for multiple users.

For the hybrid beamforming design of this disclosure, the user equipment(UE) spatial channel vectors on all subcarriers are aggregated andsubsequently linearly decomposed by singular value decomposition (SVD)into wideband sub-spatial channel vectors. The channel truncation isperformed by selecting the best, i.e. those that exhibit the highestvalues, wideband sub-spatial channel vectors for each UE. The truncatedchannels are used to generate a linear analog beamforming and digitalbeamforming. In this manner, the constraint of the given number ofantenna ports and antenna elements can be satisfied, and the analogbeamforming is wideband for multiple users.

FIG. 1 shows a communication network 100 in an aspect of thisdisclosure. It is appreciated that communication network 100 isexemplary in nature and may thus be simplified for purposes of thisexplanation.

Communication Network 100 may be configured in accordance with thenetwork architecture of any one of, or any combination of, 5G, LTE (LongTerm Evolution), WLAN (wireless local area network), WiFi, UMTS(Universal Mobile Telecommunications System), GSM (Global System forMobile Communications), Bluetooth. CDMA (Code Division Multiple Access),Wideband CDMA (W-CDMA), etc.

Base station 110 may be associated with a radio access section ofcommunication network 100, i.e. the Radio Access Network (RAN) ofcommunication network 100. Base station 110 may thus act as an interfacebetween the RAN of communication network 100 and an underlying corenetwork of communication network 100 and may allow any proximate UEs,such as, for example, UEs 120-126 to exchange data with the core networkof communication network 100.

Communication network 100 may by an LTE network, in which case, basestation 110 may be an eNB. eNB 110 may have a corresponding coverageregion 115. Coverage region 115 may comprise of a single cell (pictured)or a cluster of cells (not pictured), i.e. coverage region 115 may besectorized. eNB 110 is responsible for providing coverage region 115with access to the communication network. eNB 110 may comprise bothantenna ports and antenna elements in order to implement a hybridbeamforming scheme. Communication network 100 may also comprise UEs120-126, which are within the coverage region provided by base station110.

eNB 110 may be configured to implement a hybrid beamforming scheme 130a-130 d in order to receive or transmit communications with each of UEs120-126. Beamforming is a technique used in wireless communications fordirectional signal transmission and/or reception. it combines elementsin a phased array so that the signals constructively interfere atcertain angles while other angles experience destructive interference.In this manner, a beamforming scheme can concentrate a signal to atarget location, i.e. a particular UE location. In this disclosure, thebase stations (i.e. the eNBs) or other communication devices (e.g. UEs,tablets, computers, etc.) implement a hybrid beamforming scheme, i.e.the eNB/devices beamform with both digital elements (the antenna ports,or the RF chains) and with analog elements (the antenna elements, whichcomprise phase shifters), using a linear algorithm in the preceding.

Current hybrid beamforming methods present drawbacks that thisdisclosure is able to avoid. For example, in one current implementation,the analog beamforming is fixed and set according to a down-tilt in theantenna array. While the precoding complexity of this implementation maybe low, the overall system performance is low as well. In anotherexample, the analog beamforming is not fixed, but both the analog anddigital beamforming are generated by nonlinear algorithms throughiteration optimizations or exhaustive searches. While this formatprovides for high system performance, it also presents the problem ofvery high precoding complexity, especially when applied to moderncommunication systems. The disclosure herein is able to achieve highsystem performance with a low precoding complexity.

FIG. 2 shows a communication network 200 with base stations, 210-214,corresponding cells, 220-224, which serve UEs 230-234 c. It isappreciated that communication network 200 is exemplary in nature andmay thus be simplified for purposes of this explanation.

In communication network 200, both base stations 210-214 and UEs 230-234c are capable of hybrid beamforming, i.e. they both have at least one RFchain and multi-antenna arrays. In this manner, all the communicationsdevices (i.e. the base stations and the UEs) are configured to implementthe methods disclosed herein.

FIG. 3 shows an internal arrangement for a system model 300 for acommunication device which is configured to implement a hybridbeamforming scheme to communicate with other devices in an aspect ofthis disclosure. It is appreciated that system model 300 is exemplary innature and may thus be simplified for purposes of this explanation.

The digital domain of the base station consists of a plurality ofantenna ports, 310-312. In this example, two antenna ports are shown(i.e. L=2), but it appreciated more systems with more antenna ports areincluded in this disclosure, i.e. L>2. Each antenna port consists of anRF chain, which may comprise RF devices such as transmitters, receivers,cables, amplifiers, attenuators, measurement instruments, loads, Digitalto Analog Converters (DACs), Analog to Digital Converters (ADCs), etc.The antenna ports are connected to an array of N antenna elements,330-337, which operate in the analog domain. In antenna system model300, there are eight antenna elements shown, i.e. N=8, but it isappreciated that other quantities of antenna elements may be implementedin this disclosure. Phase shifters (a first set in the column under 315and a second set in the column above 325) control the phase of thesignal transmitted by each antenna element 330-337 in analog beamformingby manipulating the analog beamforming weight. By applying a phase shiftto the signals transmitted by the antenna elements 330-337, thedirection of constructive interference may be manipulated as required.The amplitudes and phases of the signals may be adjusted by applyingsuitable antenna weights.

A baseband unit (i.e. baseband controller) 340 is connected to the radiofrequency unit (encompassing antenna ports 310-320 and antenna elements330-337) of eNB 300 and may perform the baseband processing of mobilecommunication signals. Baseband unit 340 may further provide or receivedigital mobile communication signals to or from at least one antennaport or antenna element. Elements 310-337 may be responsible for radiofrequency processing of mobile communication signals and may includedigital (e.g. the antenna ports 310-320) as well as analog circuitry(e.g. the antenna elements 330-337) in order to receive and performinitial processing on wireless radio frequency signals. The basebandunit 340 may exchange digital mobile communication data with one or moreantenna ports or antenna elements over an optical fiber or similarhigh-speed connection, such as using a Common Public Radio Interface(CPRI) standard over an optical fiber data link.

It is understood that the components of base station 300 and allinternal components thereof (e.g. the baseband hardware, radio frequencyhardware, memory components, compression components, etc.) may bestructurally implemented as hardware, software executed on hardware or amixture thereof. Specifically, baseband unit 340 and radio frequencyunits 310-337 may include one or more digital processing circuits, suchas logic circuits, processors, microprocessors, Central Processing Units(CPUs), Graphics Processing Units (GPUs) (including General-PurposeComputing on GPU (GPGPU)), Digital Signal Processors (DSPs), FieldProgrammable Gate Arrays (FPGAs), integrated circuits, ApplicationSpecific Integrated Circuits (ASICs), or any combination thereof. It isunderstood that a person of skill in the art will appreciate thecorresponding structure disclosed herein, be it in explicit reference toa physical structure and/or in the form of mathematical formulas, prose,flow charts, or any other manner providing sufficient structure (such ase.g. regarding an algorithm). The components of base station 300 may bedetailed herein substantially in terms of functional operation inrecognition that a person of skill in the art may readily appreciate thevarious possible structural realizations of each component that willprovide the desired functionality.

While the description may focus on the downlink or uplink path, it isunderstood that base station 300 may additionally be capable of ineither direction.

Base station 300 may receive wireless uplink signals using antenna array330-337. An analog combiner may then combine the resulting uplink datasignals, such as by combining the uplink data signals from sets of twoor more antennas of antenna array 330-337 in the analog domain. Analogcombiner may thus yield analog data streams which indicate the number ofanalog data streams produced by analog combiner, which may be equal toor less than the actual number of physical receive antennas in antennaarray 330-337.

Base station 300 may process the analog data streams received fromanalog combiner using processing circuitry. It may perform automaticgain control (AGC) and analog-to-digital conversion (ADC) on the analogdata streams received from analog combiner and subsequently perform FastFourier Transform (FFT) processing in order to generate frequency domainsymbols in the antenna ports 310-320.

Base station 300 may therefore further include channel estimation (CE)and compression hardware, which may be composed of digital processingcircuitry in the antenna ports 310-320 and may thus require extracalculation and processing hardware, which may be utilized in order toperform channel estimation and calculate compression filters.

Baseband unit 340 may receive the data and perform equalization andcoordinated processing. Baseband unit 340 may include digital processingcircuitry and memory components, among other components.

The baseband unit 340 may be configured to implement any of theprocesses disclosed herein, including, but not limited to, channeltruncation, analog beamforming generation, and/or digital beamforminggeneration.

Controller 350 may be connected to the baseband unit 340 and may beconfigured, among other things, to control higher level processing.

As shown in FIG. 3, the hybrid antenna system model 300 has a fullconnection mode between its N antenna elements 330-337 and L antennaports 310-320. Without loss of generality, the design disclosed hereinis explained by assuming that each UE has a single antenna, but thedisclosure herein may easily be extended for multi-antenna UEs.

The hybrid precoding for k number UEs on a subcarrier f is given as(1≤k≤K and 1≤f≤C):u _(f,k) =U _(AB) u _(DB,f,k)  (1)Where U_(AB) is the analog beamforming matrix of size N×L, u_(DB,f,k) isthe digital beamforming vector of L×1, and K≤L≤N. The analog beamformingmatrix is wideband and implemented by phase shifters. The spatialchannel vector between UE k and eNB on subcarrier f is denoted ash_(f,k) which is of size N×1.

FIG. 4 is a block diagram 400 showing a hybrid precoding in an aspect ofthis disclosure. It is appreciated that diagram 400 is exemplary innature any may thus be simplified for purposes of this explanation.

The hybrid precoding design disclosed herein comprises three mainmodules: channel truncation 402, analog beamforming generation 404, anddigital beamforming generation 406.

In the channel truncation 402, the UE spatial channel vectors (h_(f,k))on each subcarrier f are aggregated across all subcarriers C, and thenlinearly decomposed by SVD into wideband sub-spatial channel vectors.Then, channel truncation is performed by selecting only the best ofthese wideband sup-spatial vectors to each UE.

In the analog beamforming generation 404, the truncated channels from402 are used to generate the linear analog beamforming that is widebandfor multiple users. In doing so, the constraint given by the number ofantenna ports and antenna elements can be satisfied. Similarly, thedigital beamforming generation 406 also uses the truncated channelsdetermined in 402 to generate the digital beamforming.

Each of modules of the precoding design are explained in more detail inFIG. 5-7.

FIG. 5 shows a block diagram 500 showing the details of channeltruncation (i.e., 402 in FIG. 4) in an aspect of this disclosure. It isappreciated that diagram 500 is exemplary in nature and may thus besimplified for purposes of this explanation.

In 502, the spatial channel vectors of UE k are aggregated over all thescheduled subcarriers:H _(k)=[h _(1,k) , . . . ,h _(C,k)]  (2)where h_(1,k) is the first spatial channel vector for subcarrier 1 forUE k and h_(C,K) is the final spatial channel vector for subcarrier Cfor UE k. H_(k) is a matrix of size N×C.

After the spatial channel vectors are aggregated, the singular valuedecomposition (SVD) is performed on H_(k) 504

$\begin{matrix}{H_{k} = {\sum\limits_{p_{k} \in \Phi_{k}}{\lambda_{p_{k}}\mu_{p_{k}}v_{p_{k}}^{H}}}} & (3)\end{matrix}$where p_(k) is the index for the p-th largest singular value; Φ_(k) isthe index set of eigenvalues in H_(k); r_(k)=|Φ_(k)| is the column rankof H_(k); λ_(p) _(k) is the singular value in a descending order, μ_(p)_(k) is the left singular vector, and ν_(p) _(k) is the right singularvector.

From the SVD, the left singular vectors, μ_(p) _(k) , may be viewed aswideband sub-spatial channel vectors since the spatial directions arethe same across all the subcarriers. The right singular vectors, ν_(p)_(k) ^(H), which have elements varying over subcarriers, correspond tothe frequency responses for wideband sub-spatial channel vectors.

The aggregated spatial channel matrix, H_(k), is truncated 506 bykeeping only {circumflex over (r)}_(k) singular values as:

$\begin{matrix}{{\hat{H}}_{k} = {{\sum\limits_{p_{k} \in \Phi_{k}}{\lambda_{p_{k}}\mu_{p_{k}}v_{p_{k}}^{H}}} = \left\lbrack {{\hat{h}}_{1,k},\ldots\mspace{14mu},{\hat{h}}_{C,k}} \right\rbrack}} & (4)\end{matrix}$

The rank {circumflex over (r)}_(k)=|{circumflex over (Φ)}_(k)| of thetruncated channel Ĥ_(k) can be different from UE to UE, but the sumconstraint must be met, i.e. Σ_(k=1) ^(K){circumflex over (r)}_(k)=L,where L is the number of antenna ports of the hybrid beamforming antennasystem, a basic constraint to the channel truncation of this disclosure.

The allocation of {circumflex over (r)}_(k) and the setting of{circumflex over (Φ)}_(k) to each UE is a design option which may bevaried depending on the usage case. For example, in one usage case, tomaximize the rate of UE k, the first {circumflex over (r)}_(k)-strongesteigenvalues are selected in the channel truncation to UE k. For example,the first X strongest (i.e. highest) eigenvalues may be selected forchannel truncation, where X is an integer greater than zero but lessthan the number of total eigenvalues.

If the truncated channel has the rank sum constrained as

${{\sum\limits_{k = 1}^{K}{\hat{r}}_{k}} = L},$the aggregated full linear digital precoder U=[U₁, . . . , U_(C)] has acolumn rank no larger than L. Any linear digital MU-MIMO precoder onsubcarrier f, e.g. by zero-forcing (ZF) or minimum mean squared error(MMSE), is a linear combination of all UE's spatial channel vectors onsubcarrier f. Thus, the rank of U_(f) is identical to the rank oftruncated channel H_(f). Because Ĥ_(f) for different subcarrierscontains the same selected wideband sub-spatial channel vectors, allĤ_(f) for f=1, . . . , C span the same column space as [Ĥ₁, . . . ,Ĥ_(K)], which means the full digital precoder U=[U₁, . . . , U_(C)] hasa column rank identical to [Ĥ₁, . . . , Ĥ_(K)], i.e.

${\sum\limits_{k = 1}^{K}{\hat{r}}_{k}} = {L.}$This factor indicates that the channel truncation shown in FIG. 5guarantees that the analog and digital beamforming generation generatesa hybrid precoding which satisfies the constraint by the hybrid antennaarray.

The strategies of channel truncation, i.e. the allocation of {circumflexover (r)}_(k) and the setting of {circumflex over (Φ)}_(k) to each UEcan be chose based on usage cases. The strategies of channel truncation,i.e. choosing the wideband sub-spatial channel vectors and thecorresponding strengths can be varied to achieve the defined optimalityin different usage cases. Two examples illustrate this point below.

The first example is a gain-optimal based truncation. The channeltruncation only keeps the wideband sub-spatial channel vectors with thefirst L-largest eigenvalues.

The second example is a capacity-optimal based truncation, which denotesthe sum rate of MU-MIMO on subcarrier f under a given allocation profile{circumflex over (r)}_(k) as R_(f)({circumflex over (Φ)}₁, . . . ,{circumflex over (Φ)}_(K)), then the strategy is to solve theoptimization:

$\begin{matrix}{\max\limits_{{\sum\limits_{k = 1}^{K}\;{}} = L}{\sum\limits_{f = 1}^{C}{R_{f}\left( {,\ldots\mspace{14mu},} \right)}}} & (5)\end{matrix}$where greedy optimization can be applied to achieve a linear complexityin order to make the truncation selection.

FIG. 6 shows a block diagram 600 showing the details for analogbeamforming generation (i.e. 404 in FIG. 4) in an aspect of thisdisclosure. It is appreciated that diagram 600 is exemplary in natureand may thus be simplified for purposes of this disclosure.

In 602, the truncated spatial channel vectors of all K UEs on subcarrierf are aggregated as:Ĥ _(k)=[ĥ _(f,1) , . . . ,ĥ _(f,K)]  (6)which is of size N×K.

The linear precoding vector u_(f,k) of UE k on subcarrier f is linearlycalculated 604 from the truncated channels, ĥ_(f,k). Specifically, ifzero-forcing (ZF) and minimum mean squared error (MMSE) beamforming areconsidered, the multiple user-MIMO (MU-MIMO) precoder on subcarrier fcan be found, respectively, as:U _(f)=[u _(f,1) , . . . ,u _(f,K)]=(Ĥ _(f) ^(H) Ĥ _(f))⁻¹ Ĥ _(f)^(H)  (7)U _(f)=[u _(f,1) , . . . ,u _(f,K)]=(Ĥ _(f) ^(H) Ĥ _(f) +R _(n))⁻¹ Ĥ_(f) ^(H)  (8)where R_(n) is the receiver noise matrix.

The overall MU-MIMO precoder is aggregated over all of the subcarriers606 asU=[U ₁ , . . . ,U _(C)]  (9)which is of size N×KC.

Then, taking a short SVD of rank L to U 608:U=U _(A) DV  (10)where U_(A) us of size N×L and V=[V₁, . . . , V_(C)].

The analog beamforming matrix is then constructed 610 asU _(AB)=2U _(A) diag[d ₁ ⁻¹ , . . . ,d _(L) ⁻¹]  (11)whered _(l)=max|U _(A)(i,l)|; 1≤i≤N  (12)is the maximum absolute value of the elements in the lth column of U_(A)and 1≤l≤L.

In order to transform the analog beamforming matrix (U_(AB)) to meet therequirement of having elements with only phases, U_(AB) is transformedinto a product matrix Û_(AB) of size N×2L and a matrix D_(AB) of size2L×L. The elements of Û_(AB) are given by:

$\begin{matrix}{{{\hat{U}}_{AB}\left( {n,{{2j} - 1}} \right)} = e^{i({{phase}({{U_{AB}{({n,j})}} - {\cos^{- 1}{(\frac{{abs}({U_{AB}{({n,j})}})}{2d_{j}})}}}}}} & (13)\end{matrix}$

$\begin{matrix}{{{\hat{U}}_{AB}\left( {n,{2j}} \right)} = e^{i({{phase}({{U_{AB}{({n,j})}} + {\cos^{- 1}{(\frac{{abs}({U_{AB}{({n,j})}})}{2d_{j}})}}}}}} & (14)\end{matrix}$where n=1, . . . , N and j=1, . . . , L.

The matrix of D_(AB) is given by

$\begin{matrix}{D_{AB} = \begin{bmatrix}d_{1} & \ldots & 0 \\d_{1} & \ldots & 0 \\0 & \ldots & 0 \\\ldots & \ldots & \ldots \\0 & \ldots & d_{L} \\0 & \ldots & d_{L}\end{bmatrix}} & (15)\end{matrix}$

By setting U_(AB)=Û_(AB)D_(AB), the matrix U_(AB) can be implemented byphase-shifters in the hybrid antenna array, and D_(AB), which has Lpositive scalars, can be implemented by L analog to digital converters(ADCs) in the RF chains of the antenna ports.

Any digital precoder U_(AB) of size N×L can be implemented by using N×2Lphase shifters and L ADCs, i.e. U_(AB)=Û_(AB)D_(AB), where Û_(AB) andD_(AB) are determined as specified in FIG. 6. This holds true in anycase. Therefore, it ensures the designed analog beamforming matrixU_(AB) from FIG. 6 can be implemented by N×2L phase-shifters andequivalently viewed as analog beamforming.

FIG. 7 shows a block diagram 700 showing the details for digitalbeamforming generation (i.e. 406 in FIG. 4) in an aspect of thisdisclosure. It is appreciated that diagram 700 is exemplary in natureand may thus be simplified for purposes of this disclosure.

After the analog beamforming generation, the digital beamforming vectorfor UE k on subcarrier f is calculated 702 asu _(DB,f,k)=(U _(AB) ^(H) U _(AB))⁻¹ U _(AB) ^(H) u _(f,k)  (16)which is of size L×1. Then, the digital beamforming vector can be scaled704 as normalized byu _(DB,f,k)=η_(f,k) u _(DB,f,k)  (17)where η_(f,k) is a scalar.

If the MU-MIMO precoder U=[U₁, . . . , U_(C)] of size N×KC aggregatedfrom all of the subcarriers has a column rank no larger than L. U can beimplemented by using a hybrid antenna array structure, i.e., the overallMU-MIMO precoder on subcarrier f is U_(f)=U_(AB)[u_(DB,f,1), . . . ,u_(DB,f,K)]. This is supported by the SVD of U=U_(A)DV, where U_(A) isof size N×L due to the rank constraint. The analog beamforming matrixU_(AB) is constructed as shown in FIG. 6, and the digital beamformingmatrix u_(DB,f,k) is constructed as shown in FIG. 7.

As shown in FIG. 6, the part of precoding U_(AB) can be implemented byN×2L phase-shifters and L ADCs in the antenna ports. Then, the remainingpart [u_(DB,f,1), . . . , U_(DB,f,K)], can be implemented as digitalMU-MIMO precoders on subcarrier f by L antenna ports.

If the full digital precoder has a column rank no larger than L, FIGS. 6and 7 provide a hybrid precoding design that can be applied in thehybrid beamforming system.

FIG. 8 shows a graph 800 depicting simulation results for a designedhybrid precoding in this disclosure.

Simulation results are reported for a designed hybrid precoding with 64antenna elements (i.e. N=64) and 3 UEs (i.e. K=3). The channeltruncation in the design of this aspect of the disclosure is based on aimplementing a greedy algorithm to optimize the capacity. The ZFprecoding algorithm is applied to both a full digital beamforming (DB)system and the hybrid beamforming (HB) systems. The physical channelsare generated according to 3GPP TR 36.873.

The line marked with the circles in graph 800 shows the simulationresults of the full DB system. While the performance of the full HBsystem is the highest, the complexity of the precoding design is alsoextremely high.

However, by implementing the design disclosed herein with only 6 antennaports (i.e. L=6), as shown by the line marked with the invertedtriangles, the HB system of this disclosure shows only a 2 bps/Hzcapacity loss to the full DB system with a significant reduction inprecoding complexity. Even by using four antenna ports (L=4, line markedwith diamonds) or even three antenna ports (L=3, line marked withtriangles), there is less than a 4 bps/Hz capacity loss at 20 dB channelsignal to noise ratio (SNR).

In contrast, the HB system using fixed but randomly-chosen phases inanalog beamforming, while providing the benefit of low computationalcomplexity when compared to the full DB system, shows a sum rate of lessthan 4 bps/Hz, or markedly less than half of the rate by using thedesigned hybrid precoding design of this disclosure.

FIG. 9 shows a circuit diagram 900 for the baseband unit 340 of acommunication device depicting the components related to hybridbeamforming precoding in an aspect of this disclosure. It is appreciatedthat circuit diagram 900 is exemplary in nature and may thus besimplified for purposes of this explanation.

The baseband unit 340 (or similarly, a physical layer processing circuitof the communication device) may include channel truncation circuitry910, which may, for example, include aggregation circuitry, circuitryconfigured to determine the SVD, and truncation circuitry configured toselect highest value from the SVD. The channel truncation circuitry 910may be configured to implement the method described in FIG. 5

The baseband unit 340 may further include analog beamforming circuitry920, which may include aggregation circuitry, linear precodingcircuitry, SVD calculation circuitry, and analog beamforming calculationcircuitry. Analog beamforming circuitry 920 may be configured toimplement the method described in FIG. 6.

The baseband unit 340 may further include digital beamforming circuitry930, which may include digital beamforming vector generation circuitryand digital beamforming vector scaling circuitry. Digital beamformingcircuitry 930 may be configured to implement the method described inFIG. 7.

In an alternate embodiment, analog beamforming circuitry 920 and digitalbeamforming circuitry 930 may be merged into a single circuitrycomponent configured to produce both analog and digital beamformingcomponents for the hybrid beamforming precoding.

FIG. 10 shows a flowchart 1000 in an aspect of this disclosure. It isappreciated that flowchart 1000 is exemplary in nature and may thus besimplified for purposes of this explanation.

First, a plurality of spatial channel vectors received at the antennaarray are aggregated 1002. Then, a linear factorization on the resultsof the aggregation is performed 1004. After this, the results of thelinear factorization are truncated to generate truncated channels 1006.Once the truncated channels are generated, the hybrid beamforming (HB)precoding is designed utilizing the truncated channels, wherein the HBincludes analog beamforming and a digital beamforming components 1008.

In Example 1, a method adapted for designing a hybrid beamforming (HB)precoding used in a mobile communication system comprising an antennaarray, the method including: aggregating spatial channel vectorsreceived by the antenna array; performing a linear factorization of theaggregation; truncating the linear factorization to generate truncatedchannels; and designing the HB precoding based on the truncatedchannels, wherein the HB precoding includes a linearly generated analogbeamforming component; and a linearly generated digital beamformingcomponent.

In Example 2, the subject matter of Example 1 may include receiving thespatial channel vectors from at least one other device.

In Example 3, the subject matter of Examples 1-2 may include wherein theantenna array comprises at least one antenna port and a plurality ofantenna elements.

In Example 4, the subject matter of Examples 1-3 may include whereinaggregating the spatial channel vectors is done over a plurality ofsubcarriers.

In Example 5, the subject matter of Example 4 may include wherein theplurality of subcarriers comprises scheduled subcarriers for eachdevice.

In Example 6, the subject matter of Examples 1-5 may include wherein thelinear factorization comprises a singular value decomposition (SVD).

In Example 7, the subject matter of Examples 1-6 may include wherein thetruncating comprises maximizing gains at the apparatus.

In Example 8, the subject matter of Example 7 may include keeping a setof L sub-spatial wideband channel vectors, wherein L equals the numberof antenna ports of the apparatus.

In Example 9, the subject matter of Example 8 may include wherein theset comprises the sub-spatial wideband channel vectors with the largesteigenvalues.

In Example 10, the subject matter of Examples 3-9 may include whereinthe at least one antenna port comprises a radio frequency (RF) chain.

In Example 11, the subject matter of Example 10 may include wherein eachRF chain comprises at least one of an analog to digital converter (ADC),digital to analog converter (DAC) or an amplifier.

In Example 12, the subject matter of Examples 3-11 may include whereineach antenna element is coupled to at least one phase shifter.

In Example 13, the subject matter of Examples 1-6 may include whereinthe truncating comprises maximizing a beamforming capacity.

In Example 14, the subject matter of Example 13 may include whereinmaximizing the beamforming capacity comprises determining the following:

$\max\limits_{{\sum\limits_{k = 1}^{K}\;{}} = L}{\sum\limits_{f = 1}^{C}{R_{f}\left( {,\ldots\mspace{14mu},} \right)}}$wherein R_(f)=({circumflex over (Φ)}₁, . . . , {circumflex over(Φ)}_(K)) is a sum rate of a multiple-user multiple-inputmultiple-output (MU-MIMO) on a subcarrier f; K is a number of the atleast one other device; {circumflex over (Φ)}_(k) is a set ofeigenvalues of a matrix comprising the truncated channels; L is a numberof antenna ports of the apparatus; and C is the number of subcarriers.

In Example 15, the subject matter of Examples 1-14 may includecalculating a linear precoding vector for each of the at least one otherdevice on each subcarrier from the truncated channels.

In Example 16, the subject matter of Example 15 may include calculatingthe linear precoding vector for each of the at least one other device oneach subcarrier by zero-forcing.

In Example 17, the subject matter of Example 15 may include calculatingthe linear precoding vector for each of the at least one other device oneach subcarrier by minimum mean squared error beamforming.

In Example 18, the subject matter of Examples 15-17 may includeaggregating the linear precoding vector for each of the at least oneother device over the plurality of subcarriers.

In Example 19, the subject matter of Example 18 may include taking asingular value decomposition (SVD) of the aggregation of the linearprecoding vectors.

In Example 20, the subject matter of Example 19 may include constructingan analog beamforming matrix from the SVD of the aggregation of thelinear precoding vectors.

In Example 21, the subject matter of Examples 1-20 may includecalculating a digital beamforming vector for each other device.

In Example 22, the subject matter of Example 21 may include normalizingthe digital beamforming vector for each other device.

In Example 23, the subject matter of Example 22 may include wherein thenormalizing is done by multiplying the digital beamforming vector foreach other device by a scalar.

In Example 24, a communication device configured to design a hybridbeamforming (HB) precoding, including an antenna array configured toreceive spatial channel vectors from one or more devices; aggregationcircuitry configured to aggregate the received spatial channel vectors;factorization circuitry configured to perform a linear factorization ofthe aggregated received spatial channel vectors; truncation circuitryconfigured to truncate the linear factorization to generate truncatedchannels; and beamforming generation circuitry configured to generateanalog and digital beamforming components from the truncated channels.

In Example 25, the subject matter of Example 24 may include the antennaarray comprising at least one antenna port and a plurality of antennaelements.

In Example 26, the subject matter of Example 25 may include the at leastone antenna port comprising a radio frequency (RF) chain.

In Example 27, the subject matter of Example 26 may include wherein eachRF chain comprises at least one of an analog to digital converter (ADC),digital to analog converter (DAC) or an amplifier.

In Example 28, the subject matter of Examples 25-27 may include whereineach antenna element is coupled to at least one phase shifter.

In Example 29, the subject matter of Examples 24-28 may include thebeamforming generation circuitry comprising analog beamforminggeneration circuitry configured to linearly generate the analogbeamforming component from the truncated channels.

In Example 30, the subject matter of Examples 24-29 may include thebeamforming generation circuitry comprising digital beamforminggeneration circuitry configured to linearly generate the digitalbeamforming component from the truncated channels.

In Example 31, the subject matter of Examples 24-30 may include thefactorization circuitry configured to perform the linear factorizationby singular value decomposition (SVD).

In Example 32, the subject matter of Examples 24-31 may include thetruncation circuitry configured to maximize gains of the communicationdevice.

In Example 33, the subject matter of Example 32 may include thetruncation circuitry configured to keep a set of sub-spatial widebandchannel vectors with the largest eigenvalues.

In Example 34, the subject matter of Example 33 may include wherein theset comprises of L sub-spatial wideband channel vectors, where L equalsthe number of antenna ports of the communication device.

In Example 35, the subject matter of Examples 24-31 may include thetruncation circuitry configured to maximize a beamforming capacity.

In Example 36, the subject matter of Example 35 may include thetruncation circuitry configured to maximize the beamforming capacityaccording to the following

$\max\limits_{{\sum\limits_{k = 1}^{K}\;{}} = L}{\sum\limits_{f = 1}^{C}{R_{f}\left( {,\ldots\mspace{14mu},} \right)}}$wherein R_(f)=({circumflex over (Φ)}₁, . . . , {circumflex over(Φ)}_(K)) is a sum rate of a multiple-user multiple-inputmultiple-output (MU-MIMO) on a subcarrier f; K is a number of the one ormore devices; {circumflex over (Φ)}_(k) is a set of eigenvalues of amatrix comprising the truncated channels; L is a number of antenna portsof the apparatus; and C is the number of subcarriers.

In Example 37, the subject matter of Examples 24-36 may include furthercomprising calculation circuitry configured to calculate a linearprecoding vector for each of the one or more devices on each subcarrierfrom the truncated channels.

In Example 38, the subject matter of Example 37 may include thecalculation circuitry further configured to calculate the linearprecoding vector for each of the one or more devices on each subcarrierfrom the truncated channels by zero-forcing.

In Example 39, the subject matter of Example 37 may include thecalculation circuitry further configured to calculate the linearprecoding vector for each of the one or more devices on each subcarrierfrom the truncated channels by minimum mean squared error beamforming.

In Example 40, the subject matter of Examples 37-39 may include thecalculation circuitry further configured to aggregate the linearprecoding vector for each of the one or more devices over the pluralityof subcarriers.

In Example 41, the subject matter of Example 40 may include thecalculation circuitry further configured to determine a singular valuedecomposition (SVD) of the aggregation of the linear precoding vectors.

In Example 42, the subject matter of Example 41 may include thebeamforming generation circuitry configured to construct an analogbeamforming matrix from the SVD of the aggregation of the linearprecoding vectors.

In Example 43, the subject matter of Examples 24-42 may include thebeamforming generation circuitry configured to construct a digitalbeamforming vector for each of the one or more devices.

In Example 44, the subject matter of Example 43 may include thebeamforming generation circuitry configured to further normalize thedigital beamforming vector for each of the one or more devices.

In Example 45, the subject matter of Example 44 may include thebeamforming generation circuitry configured to normalize the digitalbeamforming vector for each of the one or more devices by multiplyingthe vector by a scalar.

In Example 46, a circuit arrangement adapted to design a hybridbeamforming (HB) precoding including circuitry configured to: aggregatespatial channel vectors; perform a linear factorization of theaggregated spatial channel vectors; truncate the linear factorization togenerate truncated channels; generate an analog beamforming componentfrom the truncated channels; and generate a digital beamformingcomponent from the truncated channels.

In Example 47, the subject matter of Example 46 may include circuitryconfigured to receive the spatial channel vectors from one or moredevices.

In Example 48, the subject matter of Example 47 may include thecircuitry configured to receive comprising at least one antenna port andat plurality of antenna elements.

In Example 49, the subject matter of Example 48 may include the at leastone antenna port comprising a radio frequency (RF) chain.

In Example 50, the subject matter of Example 49 may include wherein eachRF chain comprises at least one of an analog to digital converter (ADC),digital to analog converter (DAC) or an amplifier.

In Example 51, the subject matter of Examples 48-50 may include whereineach antenna element is coupled to at least one phase shifter.

In Example 52, the subject matter of Examples 47-51 may include thecircuitry configured to generate an analog beamforming component furtherconfigured to linearly generate the analog beamforming component fromthe truncated channels.

In Example 53, the subject matter of Examples 47-52 may include thecircuitry configured to generate a digital beamforming component furtherconfigured to linearly generate the digital beamforming component fromthe truncated channels.

In Example 54, the subject matter of Examples 47-53 may include thecircuitry configured to perform the linear factorization furtherconfigured to perform the linear factorization by singular valuedecomposition (SVD).

In Example 55, the subject matter of Examples 47-54 may include thecircuitry configured to truncate further configured to maximize gains ofthe communication device.

In Example 56, the subject matter of Example 55 the circuitry configuredto truncate further configured to keep a set of sub-spatial widebandchannel vectors with the largest eigenvalues.

In Example 57, the subject matter of Example 56 may include wherein theset comprises of L sub-spatial wideband channel vectors, where L equalsthe number of antenna ports of the communication device.

In Example 58, the subject matter of Examples 47-54 may include thecircuitry configured to truncate further configured to maximize abeamforming capacity.

In Example 59, the subject matter of Example 58 may include thecircuitry configured to truncate further configured to maximize thebeamforming capacity according to the following

$\max\limits_{{\sum\limits_{k = 1}^{K}\;{}} = L}{\sum\limits_{f = 1}^{C}{R_{f}\left( {,\ldots\mspace{14mu},} \right)}}$wherein R_(f)=({circumflex over (Φ)}₁, . . . , {circumflex over(Φ)}_(K)) is a sum rate of a multiple-user multiple-inputmultiple-output (MU-MIMO) on a subcarrier f; K is a number of the one ormore devices; {circumflex over (Φ)}_(k) is a set of eigenvalues of amatrix comprising the truncated channels; L is a number of antenna portsof the apparatus; and C is the number of subcarriers.

In Example 60, the subject matter of Examples 47-59 may includecircuitry configured to calculate a linear precoding vector for each ofthe one or more devices on each subcarrier from the truncated channels.

In Example 61, the subject matter of Example 60 may include circuitryconfigured to calculate the linear precoding vector for each of the oneor more devices on each subcarrier from the truncated channels byzero-forcing.

In Example 62, the subject matter of Example 60 may include configuredto calculate the linear precoding vector for each of the one or moredevices on each subcarrier from the truncated channels by minimum meansquared error beamforming.

In Example 63, the subject matter of Examples 60-62 may includecircuitry configured to aggregate the linear precoding vector for eachof the one or more devices over the plurality of subcarriers.

In Example 64, the subject matter of Example 63 may include circuitryconfigured to determine a singular value decomposition (SVD) of theaggregation of the linear precoding vectors.

In Example 65, the subject matter of Examples 46-64 may includecircuitry configured to construct an analog beamforming matrix from theSVD of the aggregation of the linear precoding vectors.

In Example 66, the subject matter of Examples 46-65 may includecircuitry configured to calculate a digital beamforming vector for eachother device.

In Example 67, the subject matter of Example 66 may include circuitryconfigured to further normalize the digital beamforming vector for eachother device.

In Example 68, the subject matter of Example 67 may include circuitryconfigured to normalize the digital beamforming vector for each otherdevice by multiplying the vector by a scalar.

In Example 69, a non-transitory computer readable medium with programinstructions, which when executed, cause a processor of a device with anantenna array to design a hybrid beamforming (HB) precoding, includingaggregating spatial channel vectors received by the antenna array,performing a linear factorization of the aggregation; truncating thelinear factorization to generate truncated channels; and designing theHB precoding utilizing the truncated channels, wherein the HB precodinginclude a linearly generated analog beamforming component; and alinearly generated digital beamforming component.

In Example 70, the subject matter of Example 69 may include receivingthe spatial channel vectors from one or more devices.

In Example 71, the subject matter of Examples 69-70 may include whereinthe antenna array comprises at least one antenna port and a plurality ofantenna elements.

In Example 72, the subject matter of Examples 69-71 may include whereinaggregating the spatial channel vectors is done over a plurality ofsubcarriers.

In Example 73, the subject matter of Example 72 may include wherein theplurality of subcarriers comprises scheduled subcarriers for eachdevice.

In Example 74, the subject matter of Examples 69-73 may include whereinthe linear factorization comprises a singular value decomposition (SVD).

In Example 75, the subject matter of Examples 69-74 may include whereinthe truncating comprises maximizing gains at the apparatus.

In Example 76, the subject matter of Example 75 may include keeping aset of L sub-spatial wideband channel vectors, wherein L equals thenumber of antenna ports of the apparatus.

In Example 77, the subject matter of Example 76 may include wherein theset comprises the sub-spatial wideband channel vectors with the largesteigenvalues.

In Example 78, the subject matter of Examples 71-77 may include whereinthe at least one antenna port comprises a radio frequency (RF) chain.

In Example 79, the subject matter of Example 78 may include wherein eachRF chain comprises at least one of an analog to digital converter (ADC),digital to analog converter (DAC) or an amplifier.

In Example 80, the subject matter of Examples 71-79 may include whereineach antenna element is coupled to at least one phase shifter.

In Example 81, the subject matter of Examples 69-74 may include whereinthe truncating comprises maximizing a beamforming capacity.

In Example 82, the subject matter of Example 81 may include whereinmaximizing the beamforming capacity comprises determining the following:

$\max\limits_{{\sum\limits_{k = 1}^{K}\;{}} = L}{\sum\limits_{f = 1}^{C}{R_{f}\left( {,\ldots\mspace{14mu},} \right)}}$wherein R_(f)=({circumflex over (Φ)}₁, . . . , {circumflex over(Φ)}_(K)) is a sum rate of a multiple-user multiple-inputmultiple-output (MU-MIMO) on a subcarrier f; K is a number of the one ormore devices; {circumflex over (Φ)}_(k) is a set of eigenvalues of amatrix comprising the truncated channels; L is a number of antenna portsof the apparatus; and C is the number of subcarriers.

In Example 83, the subject matter of Examples 69-82 may includecalculating a linear precoding vector for each of the one or moredevices on each subcarrier from the truncated channels.

In Example 84, the subject matter of Example 83 may include calculatingthe linear precoding vector for each of the one or more devices on eachsubcarrier by zero-forcing.

In Example 85, the subject matter of Example 84 may include calculatingthe linear precoding vector for each of the one or more devices on eachsubcarrier by minimum mean squared error beamforming.

In Example 86, the subject matter of Examples 83-85 may includeaggregating the linear precoding vector for each of the one or moredevices over the plurality of subcarriers.

In Example 87, the subject matter of Example 86 may include taking asingular value decomposition (SVD) of the aggregation of the linearprecoding vectors.

In Example 88, the subject matter of Example 87 may include constructingan analog beamforming matrix from the SVD of the aggregation of thelinear precoding vectors.

In Example 89, the subject matter of Examples 69-88 may includecalculating a digital beamforming vector for each other device.

In Example 90, the subject matter of Example 89 may include normalizingthe digital beamforming vector for each other device.

In Example 91, the subject matter of Example 90 may include wherein thenormalizing is done by multiplying the digital beamforming vector foreach other device by a scalar.

While the above descriptions and connected figures may depict electronicdevice components as separate elements, skilled persons will appreciatethe various possibilities to combine or integrate discrete elements intoa single element. Such may include combining two or more circuits forform a single circuit, mounting two or more circuits onto a common chipor chassis to form an integrated element, executing discrete softwarecomponents on a common processor core, etc. Conversely, skilled personswill recognize the possibility to separate a single element into two ormore discrete elements, such as splitting a single circuit into two ormore separate circuits, separating a chip or chassis into discreteelements originally provided thereon, separating a software componentinto two or more sections and executing each on a separate processorcore, etc.

It is appreciated that implementations of methods detailed herein aredemonstrative in nature, and are thus understood as capable of beingimplemented in a corresponding device. Likewise, it is appreciated thatimplementations of devices detailed herein are understood as capable ofbeing implemented as a corresponding method. It is thus understood thata device corresponding to a method detailed herein may include one ormore components configured to perform each aspect of the related method.

All acronyms defined in the above description additionally hold in allclaims included herein.

While the invention has been particularly shown and described withreference to specific embodiments, it should be understood by thoseskilled in the art that various changes in form and detail may be madetherein without departing from the spirit and scope of the invention asdefined by the appended claims. The scope of the invention is thusindicated by the appended claims and all changes which come within themeaning and range of equivalency of the claims are therefore intended tobe embraced.

What is claimed is:
 1. A circuit arrangement for a communication deviceadapted to design a hybrid beamforming (BB) precoding comprisingcircuitry configured to: aggregate spatial channel vectors; perform alinear factorization of the aggregated spatial channel vectors; truncatethe linear factorization to generate truncated channels; generate ananalog beamforming component from the truncated channels; and generate adigital beamforming component from the truncated channels.
 2. Thecircuit arrangement of claim 1, further comprising circuitry configuredto receive the spatial channel vectors from one or more devices.
 3. Thecircuit arrangement of claim 1, the circuitry configured to generate ananalog beamforming component further configured to linearly generate theanalog beamforming component from the truncated channels.
 4. The circuitarrangement of claim 1, the circuitry configured to generate a digitalbeamforming component further configured to linearly generate thedigital beamforming component from the truncated channels.
 5. Thecircuit arrangement of claim 1, the circuitry configured to perform thelinear factorization further configured to perform the linearfactorization by singular value decomposition (SVD).
 6. The circuitarrangement of claim 1, the circuitry configured to truncate furtherconfigured to maximize gains of the communication device.
 7. The circuitarrangement of claim 1, the circuitry configured to truncate furtherconfigured to maximize a beamforming capacity.
 8. The circuitarrangement of claim 1, further comprising circuitry configured tocalculate a linear precoding vector for each of the one or more deviceson each subcarrier from the truncated channels.
 9. The circuitarrangement of claim 8, further comprising circuitry configured tocalculate the linear precoding vector for each of the one or moredevices on each subcarrier from the truncated channels by zero-forcing.10. The circuit arrangement of claim 8, further comprising circuitryconfigured to calculate the linear precoding vector for each of the oneor more devices on each subcarrier from the truncated channels byminimum mean squared error beamforming.
 11. The circuit arrangement ofclaim 8, further comprising circuitry configured to aggregate the linearprecoding vector for each of the one or more devices over the pluralityof subcarriers.
 12. The circuit arrangement of claim 11, furthercomprising circuitry configured to determine a singular valuedecomposition (SVD) of the aggregation of the linear precoding vectors.13. The circuit arrangement of claim 12, further comprising circuitryconfigured to construct an analog beamforming matrix from the SVD of theaggregation of the linear precoding vectors.
 14. The circuit arrangementof claim 1, further comprising circuitry configured to calculate adigital beamforming vector for each of the one or more devices.
 15. Acommunication device configured to design a hybrid beamforming (BB)precoding, comprising: an antenna array configured to receive spatialchannel vectors from one or more devices; aggregation circuitryconfigured to aggregate the received spatial channel vectors;factorization circuitry configured to perform a linear factorization ofthe aggregated received spatial channel vectors; truncation circuitryconfigured to truncate the linear factorization to generate truncatedchannels; and beamforming generation circuitry configured to generateanalog and digital beamforming components from the truncated channels.16. The communication device of claim 15, the beamforming generationcircuitry comprising analog beamforming generation circuitry configuredto linearly generate the analog beamforming component from the truncatedchannels.
 17. The communication device of claim 15, the beamforminggeneration circuitry comprising digital beamforming generation circuitryconfigured to linearly generate the digital beamforming component fromthe truncated channels.
 18. The communication device of claim 15, thefactorization circuitry configured to perform the linear factorizationby singular value decomposition (SVD).
 19. The communication device ofclaim 15, further comprising calculation circuitry configured tocalculate a linear precoding vector for each of the one or more deviceson each subcarrier from the truncated channels.
 20. A method adapted fordesigning a hybrid beamforming (HB) precoding used in a mobilecommunication system comprising an antenna array, the method comprising:aggregating spatial channel vectors received by the antenna array;performing a linear factorization of the aggregation; truncating thelinear factorization to generate truncated channels; and designing theHB precoding based on the truncated channels, wherein the HB precodingcomprises: a linearly generated analog beamforming component; and alinearly generated digital beamforming component.
 21. The method ofclaim 20, wherein the linear factorization comprises a singular valuedecomposition (SVD).
 22. The method of claim 20, wherein the truncatingcomprises maximizing a beamforming capacity.
 23. The method of claim 20,further comprising calculating a linear precoding vector for each of theone or more devices on each subcarrier from the truncated channels. 24.A non-transitory computer readable medium with program instructions,which when executed, cause a processor of a device with an antenna arrayto design a hybrid beamforming (BB) precoding, comprising: aggregatingspatial channel vectors received by the antenna array; performing alinear factorization of the aggregation; truncating the linearfactorization to generate truncated channels; and designing the HBprecoding utilizing the truncated channels, wherein the HB precodingcomprises: a linearly generated analog beamforming component; and alinearly generated digital beamforming component.
 25. The non-transitorycomputer readable medium of claim 24, wherein the linear factorizationcomprises a singular value decomposition (SVD).